A First Principles-based Li-Ion Battery Performance and Life Prediction Model Based on Reformulated Model Equations NASA Battery Workshop Huntsville, Alabama November 17-19, 19, 2009 by Gerald Halpert 1, Venkat R. Subramanian 2, Matthew K. Heun 1, Kumar Bugga 3, and Kerry T. Nock 1 1 Global Aerospace Corporation, 711 West Woodbury Road,Suite H, Altadena, CA 91001 2 Now at Washington University, 1 Brookings Drive, St. Louis, MO 63130 6 3 Consultant - This work was funded by the Missile Defense Agency Small Business ss Technology Transfer Program under Contract HQ0006-09-C-7073. Approved for public release; distribution is unlimited. Approved for Public Release: 09-MDA-4976 (19 NOV 09).
Topics Overview Reformulated Model (RFM) Initial Set of RFM Equations Proof-of-Concept RFM Equations LEO Pulse Cycling Regime Summary Global Aerospace Corporation 2 November 17-19, 2009
Overview Program Objective - Develop a unique object-oriented Li-Ion battery model for analyzing satellite operations scenarios, Dakota, based on first principles, that describes and predicts the performance of Li-Ion cells and batteries under various operational modes and environments Why GAC and TTU? - GAC s object-oriented computer models of complex engineering systems. TTU s Li-Ion reformulated model (RFM) expertise and experience. Approach - Adapt reformulated, first-principle, cell model to an objectoriented cell / battery operations model. Verify model with LEO cycling cell test data. What s Unique? - 1. RFM fastest algorithm (as of today in the literature) developed from first-principles cell model. 2. Use of object-oriented code that is highly extensible and platform independent. 3. Engineer-friendly simulation environment. 4. Framework for a comprehensive battery model. Global Aerospace Corporation 3 November 17-19, 2009
Long-term Goals for Battery Operations Model Simulate performance and life of a cell or battery Simulate changes during operation, e.g., cell or battery imbalance in series or parallel configurations Optimize cell / battery design and configuration Assess capability for a cell or battery design to meet a mission requirement Manage battery operation for long term success Assess new cell / battery technologies Design and size power subsystems Map and simulate manufacturing processes Global Aerospace Corporation 4 November 17-19, 2009
Key Dakota Approach and Innovation and Innovation Develop an object-oriented, desktop tool based on electrochemical first-principles, useable by system engineers. (not an esoteric Fortran code with text file configuration parameter lists) Incorporate simulation of individual cell charge and discharge characteristics and cycling performance Include simulation of orbital battery operations in LEO including thermal and mechanical interactions Provide a modular architecture that allows A scalable user interface Easy what if playing New physics to be added now and in the future Cell design parameters Battery interactions with wide variety of environments Global Aerospace Corporation 5 November 17-19, 2009
Battery Modeling Projects Phase II STTR with JPL - SPM Dakota Single Particle Model (SPM) focused on LEO model development Already incorporated into Dakota engine Much faster than Full Physics Model (FPM) Limited to low rates and nominal temperatures In the prototype model development, we are extending the SPM to higher rates and a wider range of temperatures Phase I STTR with TTU - RFM Dakota Reformulated Model (RFM) focused on LEO model development Faster than FPM and handles higher rates and a wider range of temperatures like the FPM Higher fidelity at a cost of somewhat slower speed than SPM In Phase I, RFM equations for three Li-Ion chemistries were incorporated into Dakota along with the LEO orbit scenario Global Aerospace Corporation 6 November 17-19, 2009
Project Plans Selected the reformulated model (RFM) approach of Dr. Venkat R. Subramanian who was at TTU, now at Wash U. The initial objective was to develop a proof-of-concept RFM battery operations tool for a candidate Li-Ion cell chemistry focused initially on LEO Operations The RFM equations for two Li-Ion chemistries were incorporated into Dakota along with a simple LEO battery operations scenario Validated the RFM Dakota tool results against TTUgenerated charge / discharge behavior data Simulated three different pulse charge battery operations scenarios Compared pulse cycling case with no-pulse operation Global Aerospace Corporation 7 November 17-19, 2009
START ~5000 states Simplify the solid-phase diffusion equation from one PDE to few DAEs Convert the model equations to dimensionless form Choose appropriate polynomial profile solutions for dependent variables Volume averaging Galerkin collocation Closed-form derivation Intuition based reformulation Add more terms Verify with rigorous model Insufficient accuracy Sufficient accuracy Done [ V.R. Subramanian+ ESL 2007 ] <50 states Global Aerospace Corporation 8 November 17-19, 2009
Initial Set of RFM Equations Two chemistries Doyle-Newman Cell Model (LiMn 2 O 4 ) TTU / USG Cell Model (LiNi 0.8 Co 0.15 Al 0.05 O 2 ) Characteristics of test set of equations Discharge curves and dependent variables (electrolyte concentration, potential, solid-phase potential, solid-phase concentration) at x = 0. Fixed current rate Variable: State-of-charge and cutoff potential Global Aerospace Corporation 9 November 17-19, 2009
Doyle-Newman Full-Physics Model Global Aerospace Corporation 10 November 17-19, 2009
Doyle-Newman RFM Equations* * - Two of the shortest equations shown for illustration Global Aerospace Corporation 11 November 17-19, 2009
Doyle-Newman Chemistry Global Aerospace Corporation 12 November 17-19, 2009
TTU / USG Chemistry Global Aerospace Corporation 13 November 17-19, 2009
Proof-of of-concept RFM Equations Doyle-Newman Cell Model (LiMn 2 O 4 ) Charge and discharge capability Taper charging Include enough variables to enable: Initial validation of Dakota using TTU data Simulating a cell according to an example cell cycling regime Variables include: Variable current rates up to 2C Variable state-of-charge, starting and cutoff potentials Global Aerospace Corporation 14 November 17-19, 2009
Example Cycling Regime Assumptions 28 day repeating monthly period 1400 min day 14 orbits per day 100 min orbit period 35 min normal discharge 65 min normal charge (4.1 V taper) Pulse cycle scenarios Once each day (during the middle of cycle 7 discharge), pulse discharge for 0.5 min at xc, yc, or zc and Once each month pulse discharge for 10 minutes (During cycle 14 discharge on the 14th day) at xc, yc, or zc Global Aerospace Corporation 15 November 17-19, 2009
Cycling Regime Schematic Global Aerospace Corporation 16 November 17-19, 2009
Pulse and No-pulse Comparison: Current Density yc xc yc zc Global Aerospace Corporation 17 November 17-19, 2009
Pulse and No-pulse Comparison: Cell Potential yc xc yc zc Global Aerospace Corporation 18 November 17-19, 2009
Summary We have leveraged our extensive modeling and Li-Ion cell and battery expertise to develop a unique and advanced battery operations tool to predict life and performance The initial effort was aimed incorporating test set of 27 RFM equations for Doyle-Newman and TTU / USG chemistries and its results were verified with TTU Fortran/Maple results A proof-of-concept (POC) set of RFM equations for Doyle-Newman chemistry was incorporated into Dakota and its results verified A pulse power cycling regime was simulated for the POC Doyle- Newman chemistry and results compared with no-pulse operation The RFM Dakota tool now can study two chemistries under LEO cycling conditions, i.e. Doyle-Newman and TTU / USG In Phase II we propose to incorporate additional chemistries and a cell thermal model, explore degradation mechanisms, and improve the software flexibility and operability Global Aerospace Corporation 19 November 17-19, 2009
Acknowledgement Global Aerospace Corporation is appreciative of the support of MDA and specifically Dr. Harlan Lewis for his direction Global Aerospace Corporation 20 November 17-19, 2009